ArticleFrontiers in immunology2022
A novel genomic instability-derived lncRNA signature to predict prognosis and immune characteristics of pancreatic ductal adenocarcinoma.
Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 5 citations in OpenAlex.
- Development of a prognostic model related to homologous recombination deficiency in glioma based on multiple machine learning.Frontiers in immunology · 2024Article
- Long non-coding RNA signature for predicting gastric cancer survival based on genomic instability.Aging · 2023Article
- Liquid biopsy techniques and pancreatic cancer: diagnosis, monitoring, and evaluation.Molecular cancer · 2023Review
- RareWorld journal of clinical cases · 2023Article
- Molecular and metabolic regulation of immunosuppression in metastatic pancreatic ductal adenocarcinoma.Molecular cancer · 2023Review
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Authors and funding
11 authors at 4 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignant tumor of the digestive system. Its grim prognosis is mainly attributed to the lack of means for early diagnosis and poor response to treatments. Genomic instability is shown to be an important cancer feature and prognostic factor, and its pattern and extent may be associated with poor treatment outcomes in PDAC. Recently, it has been reported that long non-coding RNAs (lncRNAs) play a key role in maintaining genomic instability. However, the identification and clinical significance of genomic instability-related lncRNAs in PDAC have not been fully elucidated. Methods: Genomic instability-derived lncRNA signature (GILncSig) was constructed based on the results of multiple regression analysis combined with genomic instability-associated lncRNAs and its predictive power was verified by the Kaplan-Meier method. And real-time quantitative polymerase chain reaction (qRT-PCR) was used for simple validation in human cancers and their adjacent non-cancerous tissues. In addition, the correlation between GILncSig and tumor microenvironment (TME) and epithelial-mesenchymal transition (EMT) was investigated by Pearson correlation analysis. Results: The computational framework identified 206 lncRNAs associated with genomic instability in PDAC and was subsequently used to construct a genome instability-derived five lncRNA-based gene signature. Afterwards, we successfully validated its prognostic capacity in The Cancer Genome Atlas (TCGA) cohort. In addition, Conclusions: Our study established a genomic instability-associated lncRNAs-derived model (GILncSig) for prognosis prediction in patients with PDAC, and revealed the potential functional regulatory role of GILncSig.
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